The short answer
The pilot-to-production gap is rarely a model problem — it is an operational readiness problem. Production-ready agents need a regression eval suite, a rollout plan with kill-switches, on-call ownership, observability and logging, drift monitoring, a versioning strategy for prompts and tools, a documented human-review process, and a change-management plan for the team whose work is changing. Most pilots show working output and skip the operational layer — which is why they stall in 'evaluation purgatory' for six months.
Why pilots stall
Most pilots stall not because the agent does not work, but because nobody can articulate what 'working' means at production scale. Without a regression suite and a rollout plan, every leadership change forces a re-litigation of whether the agent is ready. The checklist below short-circuits that loop.
The production-readiness checklist
Eight items. Anything missing is a Sev-2 risk for the launch, not a 'we will figure it out in production' item.
- ›Regression eval suite: 100–300 graded examples that block any prompt or model change degrading quality.
- ›Rollout plan: cohort-based rollout (5% → 25% → 100%) with explicit go/no-go criteria per cohort.
- ›Kill-switch: documented, tested, and owned — not a Slack message asking infra to disable a service.
- ›On-call ownership: a named human who is paged when the agent misbehaves, with a runbook.
- ›Observability: structured logs of every input, output, tool call, and decision, queryable in your existing stack.
- ›Drift monitoring: weekly quality sampling and an alert when the agent's eval score drops below threshold.
- ›Versioning: prompts, tools, and model versions tracked the same way you track code — diffable, revertible.
- ›Change management: the team whose work is changing has been trained, has feedback channels, and has buy-in.
The change-management item kills the most pilots
Engineering teams over-index on the technical seven items and under-index on item eight. An agent that works perfectly but is resented by the team whose work it changes will be quietly bypassed within 90 days. Treat change management as a first-class deliverable, not an afterthought.
What a healthy pilot-to-prod handoff looks like
Eval suite green and demonstrated. Cohort plan signed off by ops leader and risk. Kill-switch tested live. On-call rotation populated for 90 days. Observability dashboard linked from the team's existing operations channel. Drift alert thresholds agreed. Versioning conventions documented. End-user team trained, with a feedback Slack channel staffed by the build team for the first 30 days.
Key takeaways
- Pilots stall on operational readiness, not on model quality.
- Eight checklist items — missing any one is a launch risk, not a nice-to-have.
- Change management is the most-skipped item and the most-lethal.
- Cohort rollouts with kill-switches beat big-bang launches every single time.
Frequently asked questions
How big should the regression eval suite be?+
Start with 100 examples covering the most common workflows and the most painful failure modes. Grow to 300+ over the first 90 days as production traffic surfaces new edge cases.
Who owns on-call for an AI agent?+
The team that built it for the first 90 days, then a joint rotation with the operating team. Pure hand-offs to ops without the build team co-paging fail because the build team loses the feedback loop.
Is kill-switch overkill for low-risk agents?+
No. Kill-switches are a five-line config; they exist so that when something unexpected happens at 2am, the responder is not making a deploy decision under stress.